MoorAI vs DeepKeep
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DeepKeep and MoorAI hook the same coding-agent events. DeepKeep decides in its own service; MoorAI decides on the machine. DeepKeep’s coding-agent plug-in, AI Lens for Developers, is described this way: “AI Lens for Developers uses existing hooks within coding agents to inspect activity before and after actions run.” and “These hooks provide checkpoints around prompts, shell commands, file reads, and MCP tool calls, routing activity to DeepKeep for an allow, block, or audit decision.” (deepkeep.ai blog, You hired a brilliant coding agent) MoorAI is a PreToolUse hook inside the coding agent and an MCP stdio proxy in front of local Model Context Protocol (MCP) servers. Its detection engine runs inside the hook, so no call to a service is needed to reach a verdict.
Both read what the agent reads, not only what the developer types. DeepKeep’s AI Lens page: “Detect credentials, tokens, and passwords in the information an agent receives and sends, including content the developer never typed into a prompt.” (deepkeep.ai/capabilities/ai-lens) The difference is what is kept. DeepKeep: “Each session also produces an audit log, including device ID, user ID, and prompt content.” (deepkeep.ai blog) MoorAI decides against a 77-threat matrix and by default sends only category · risk · keyed one-way hash; content is kept only if an administrator enables a capture tier.
DeepKeep covers far more of the AI lifecycle than MoorAI does. Its home page: “Five capabilities, one policy engine, applied everywhere GenAI touches your business.” (deepkeep.ai) Those are a runtime AI firewall for a company’s own apps and agents, red teaming, AI Lens for the workforce and developers, an agent attack-surface scanner and model scanning. MoorAI governs what coding agents do on endpoints and does none of the rest. The rows where DeepKeep covers more ground are further down.
Three things this page does not state. (1) The detail of DeepKeep’s plug-in. DeepKeep’s documentation site asks for a password (“This documentation requires a password to access”), so which hook events it registers, which fields of each event it sends and what happens when its service is unreachable are not described here; the tables mark those unconfirmed. (2) Where a customer’s DeepKeep service runs. DeepKeep says “Deployment options include VPC and on-premises environments.” (deepkeep.ai blog) The decision is made off the developer’s machine, but that can be a service the customer hosts. (3) Pricing. We found no public price list; deepkeep.ai/pricing returns a 404 and DeepKeep’s pages lead to a demo request. Every DeepKeep statement below is quoted from DeepKeep’s own site, and the page is named.
The core difference is where the verdict is reached: in a DeepKeep service the hook calls, or in the hook itself.
Where MoorAI holds ground DeepKeep does not
These rows follow from deciding inside the hook, with no content sent anywhere to reach a verdict. Several DeepKeep marks are unconfirmed, because its documentation is behind a password.
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| MoorAI | DeepKeep | |
|---|---|---|
| Reaches the verdict on the device, with no call to a service | ✓engine runs in the hook | ✗routes activity to DeepKeep for the decision |
| By default only category · risk · keyed one-way hash leave the device | ✓capture tiers are opt-in, admin-enabled | ✗audit log includes prompt content |
| Coding agents beyond Cursor and Claude Code | ◐Codex CLI, Copilot CLI, Gemini CLI adapters; not yet validated against the live agents | ✗others planned |
| Enforces for any host that launches a stdio MCP server | ✓MCP stdio proxy | —not in public material |
| Masks a secret or PII span in a coding agent’s tool call and lets it proceed | ✓mask action; not yet observed in a live Claude Code session | —the AI Firewall redacts; not stated for the coding-agent plug-in |
| MCP supply side: rug-pull knock-back, server reputation, pre-install scan of skills and MCP packages | ✓ | —not in public material |
| Flags a risky action aimed at something the user’s request never named | ✓intent alignment; lexical, keyed hashes | —not in public material |
| Same hook in CI, containers and Agent SDK services | ◐server mode; one live claude -p run watched, Agent SDK and GitHub Actions not yet | —not in public material |
| Open source, so the data claim can be checked in code | ✓agent MIT | —no published source found |
| Public product documentation, no password | ✓ | ✗docs.deepkeep.ai asks for a password |
| Free to start and to enforce, without talking to sales | ✓agent free; console free to 200 users | ✗no public pricing; demo-led |
Where DeepKeep covers ground MoorAI does not
This list is longer. DeepKeep secures a company’s own AI apps, agents and models from build to runtime, and governs workforce AI use. MoorAI governs coding agents on endpoints.
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| MoorAI | DeepKeep | |
|---|---|---|
| Runtime firewall for the company’s own AI apps and agents, inline or out-of-band | ✗ | ✓AI Firewall |
| Guardrails across text, images and video | ◐on-device OCR of pasted images; instructions hidden in pixels or video not covered | ✓ |
| Model scanning: malware, tampering and dependency vulnerabilities in model files, with MLBOM output | ✗ | ✓LLMs and computer vision models |
| Red teaming of the customer’s own apps, agents and models, automated or human-steered | ◐moorai-redteam runs a fixed corpus against MoorAI’s own policy | ✓Vibe AI Red Teaming |
| Attack-surface map of a built agent (n8n, LangChain, CrewAI, Dify and others) | ✗ | ✓AI Agent Scanner |
| Workforce AI discovery with identity-provider, role-based access to AI services | ◐on-device AI bill of materials and shadow-AI inventory; no identity-provider policy | ✓ |
| The prompt sequence of a session kept for investigation | ◐only with an opt-in capture tier | ✓ |
| Air-gapped deployment of the vendor service | —no service needed to decide; console air-gap not documented | ✓ |
Same capability, different mechanism
Both products do each of these, so the table describes how rather than scoring.
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| MoorAI does it by… | DeepKeep does it by… | |
|---|---|---|
| Stopping a coding agent’s action before it runs | A PreToolUse hook in the agent’s own process, validated end to end on Claude Code. Codex CLI, Copilot CLI, Gemini CLI and Cursor block through their own pre-tool hooks and are not yet validated against the live agents. An MCP stdio proxy enforces for any host that launches a stdio MCP server. | A plug-in on the agent’s existing hooks that sends each event to DeepKeep for allow, block or audit: “AI Lens for Developers supports Cursor and Claude Code today. Support for GitHub Copilot, OpenAI Codex, Lovable, Windsurf, and additional tools is planned.” (deepkeep.ai blog) |
| Destructive shell commands | A destructive-command rule answered by policy with coach, ask, block or session kill, judged on the device before the command runs. | “It can also flag destructive shell commands and send them to the developer for approval before they run.” (deepkeep.ai blog) |
| Sensitive data and insecure code | Secret, PII and PHI detectors on file reads, commands, MCP arguments and results; AI output review flags insecure code the agent generates (SQL injection, command injection, unsafe deserialization and more). | Credentials, tokens, passwords and PII in what the agent reads and sends, plus “custom key-phrase detection to flag sensitive code sections or internal repositories by name”; and “AI Lens can flag insecure code patterns in agent output, such as a function missing authentication.” (deepkeep.ai blog) |
| Keeping developers from switching it off | Claude Code’s managed settings can force-enable the MoorAI plugin, and the server-mode example registers the hooks there; a user, project or local settings file cannot set MoorAI’s trust anchors. | “AI Lens is centrally managed by the administrators responsible for the coding agents. Developers cannot disable it.” (deepkeep.ai blog) |
| Evidence of a decision | A signed, content-free decision receipt per verdict (tool, category, risk, decision and one-way hashes, signed with ed25519) and a hash-chained on-device log. | A session audit log with device ID, user ID and prompt content, reviewable as a sequence of attempts. |
MITRE ATLAS, as documented. In our reading of vendor material against the 76 ATLAS techniques tagged Agentic AI, DeepKeep’s published material documents 9 of the 76 (read 1 October 2026), 5 of them with a limit the vendor states, such as the coding-agent hooks covering Cursor and Claude Code only, and destructive commands sent for the developer’s approval rather than blocked outright. That counts what the public material says; DeepKeep’s product documentation is behind a password and was not read. The method and every quote behind the number are in What vendors actually document against MITRE ATLAS.
Where MoorAI is stronger. Where the verdict is reached, and what is kept. The file read, the shell command, the MCP argument and result are judged in the hook on the device, and the console receives no content. MoorAI also reaches further on coding agents (adapters for Codex CLI, Copilot CLI and Gemini CLI, and an MCP stdio proxy for any host), guards the MCP supply side, flags actions aimed outside the user’s stated task, runs the same hook in CI and containers through server mode, and is MIT code that is free to enforce up to 200 users.
Where DeepKeep is stronger. Breadth across the AI lifecycle. A runtime firewall for a company’s own AI apps and agents; guardrails that DeepKeep positions as multimodal and multilingual (“DeepKeep provides strong multilingual coverage with consistent detection and enforcement across languages.” (deepkeep.ai/capabilities/ai-firewall)); model scanning for LLMs and computer vision models; red teaming in which “Reddy, DeepKeep's AI red teaming agent, adapts attack paths in real time while you steer at each decision point.” (deepkeep.ai/capabilities/ai-red-teaming); an attack-surface scanner for agents built on low-code platforms; workforce AI discovery tied to the identity provider; and a session record a security team can investigate. If the job is securing the AI a company builds, DeepKeep is the larger product and MoorAI is not one.
Which to run where. Run DeepKeep where the question is the AI the company builds and buys: its apps, agents and models, tested before release and guarded at runtime, and workforce use of AI services. Run MoorAI on developer machines where the question is what a coding agent is about to read, run or send, and where the prompts should not leave the machine to be judged. Both hook the same coding-agent events, so running both on one machine means two hooks on every action; neither’s public material addresses that, and we have not run them together.
Questions about MoorAI and DeepKeep
Does DeepKeep decide on the developer’s machine?
No, per DeepKeep: its coding-agent plug-in uses the agent’s existing hooks and routes activity to DeepKeep for an allow, block or audit decision, and DeepKeep’s deployment options include VPC and on-premises environments. MoorAI reaches its verdict inside the hook on the device and sends no content to do so.
Which coding agents does DeepKeep AI Lens support?
Cursor and Claude Code today, per DeepKeep, with GitHub Copilot, OpenAI Codex, Lovable, Windsurf and additional tools planned. MoorAI is validated end to end on Claude Code; its Codex CLI, Copilot CLI, Gemini CLI and Cursor adapters block through each agent’s own pre-tool hooks and are not yet validated against the live agents, and its MCP stdio proxy covers any host that launches a stdio MCP server.
Does DeepKeep keep the prompt content of coding-agent sessions?
DeepKeep says each session produces an audit log that includes device ID, user ID and prompt content. MoorAI sends a category, a risk level and a keyed one-way hash by default, and keeps content only if an administrator enables a capture tier.
Does MoorAI replace DeepKeep, or the other way round?
Not as a whole. DeepKeep also sells an AI firewall for a company’s own apps and agents, red teaming, an agent attack-surface scanner and model scanning, and MoorAI does none of that. On coding agents the two overlap, and the difference is where the decision is made and what is kept.
Who backs DeepKeep?
DeepKeep says it initially raised $10M in seed funding in a round led by Awz Ventures, announced when it came out of stealth in Tel Aviv on 1 May 2024.
DeepKeep capabilities are taken from DeepKeep’s own published material, checked on 1 October 2026: deepkeep.ai, You hired a brilliant coding agent. Who supervises it?, AI Lens, AI Firewall, AI Red Teaming, AI Agent Scanner, Model Scanning, DeepKeep comes out of stealth and docs.deepkeep.ai (password-protected; not read). Every quoted phrase is DeepKeep’s. ◐ = partial: present but narrower than the other column. — = unconfirmed, not necessarily absent. MoorAI marks reflect shipped capability: hook enforcement is validated end to end on Claude Code; Codex, Copilot CLI, Gemini CLI and Cursor block through their own pre-tool hooks and are not yet validated against the live agents. Server mode (CI, containers, Agent SDK) was proven on one live claude -p run; an Agent SDK service and a GitHub Actions run have not been watched end to end. The agent is MIT and runs on macOS, Windows and Linux; the console is source-available under the Elastic License 2.0 and free up to 200 users. DeepKeep is a trademark of its owner; this page is independent and is not affiliated with or endorsed by DeepKeep. Both products change, so check specifics against current documentation.